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PSIque: Next Sequence Prediction of Satellite Images using a Convolutional Sequence-to-Sequence Network
Predicting unseen weather phenomena is an important issue for disaster management.
DeepRain: ConvLSTM Network for Precipitation Prediction using Multichannel Radar Data
This model predicts the amount of rainfall from weather radar data, which is three-dimensional and four-channel data, using convolutional LSTM (ConvLSTM).
GlobeNet: Convolutional Neural Networks for Typhoon Eye Tracking from Remote Sensing Imagery
Advances in remote sensing technologies have made it possible to use high-resolution visual data for weather observation and forecasting tasks.
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